Error mitigation with Clifford quantum-circuit data

Piotr Czarnik; Andrew Arrasmith; Patrick J. Coles; Lukasz Cincio

doi:10.22331/q-2021-11-26-592

Error mitigation with Clifford quantum-circuit data

Piotr Czarnik, Andrew Arrasmith, Patrick J. Coles, and Lukasz Cincio

Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

Published:	2021-11-26, volume 5, page 592
Eprint:	arXiv:2005.10189v3
Doi:	https://doi.org/10.22331/q-2021-11-26-592
Citation:	Quantum 5, 592 (2021).

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Abstract

Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum computers. The method generates training data $\{X_i^{\text{noisy}},X_i^{\text{exact}}\}$ via quantum circuits composed largely of Clifford gates, which can be efficiently simulated classically, where $X_i^{\text{noisy}}$ and $X_i^{\text{exact}}$ are noisy and noiseless observables respectively. Fitting a linear ansatz to this data then allows for the prediction of noise-free observables for arbitrary circuits. We analyze the performance of our method versus the number of qubits, circuit depth, and number of non-Clifford gates. We obtain an order-of-magnitude error reduction for a ground-state energy problem on 16 qubits in an IBMQ quantum computer and on a 64-qubit noisy simulator.

► BibTeX data

@article{Czarnik2021errormitigation,
  doi = {10.22331/q-2021-11-26-592},
  url = {https://doi.org/10.22331/q-2021-11-26-592},
  title = {Error mitigation with {C}lifford quantum-circuit data},
  author = {Czarnik, Piotr and Arrasmith, Andrew and Coles, Patrick J. and Cincio, Lukasz},
  journal = {{Quantum}},
  issn = {2521-327X},
  publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}},
  volume = {5},
  pages = {592},
  month = nov,
  year = {2021}
}

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